ACM Transactions on Programming Languages and Systems (TOPLAS)
Distributed discrete-event simulation
ACM Computing Surveys (CSUR)
Stochastic simulation
Performance models of multiprocessor systems
Performance models of multiprocessor systems
Performance Analysis of Parallel Processing Systems
IEEE Transactions on Software Engineering
Wolf: a rollback algorithm for optimistic distributed simulation systems
WSC '88 Proceedings of the 20th conference on Winter simulation
Statistical analysis of parallel simulations
WSC '86 Proceedings of the 18th conference on Winter simulation
Multimicroprocessors
On the Execution of Programs by Many Processors
Performance '83 Proceedings of the 9th International Symposium on Computer Performance Modelling, Measurement and Evaluation
Scheduling partially ordered tasks with probabilistic execution times
SOSP '75 Proceedings of the fifth ACM symposium on Operating systems principles
Parallel discrete event simulation
Communications of the ACM - Special issue on simulation
Asynchronous algorithms for the parallel simulation of event-driven dynamical systems
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Multitasking simulation of a boiler system using qualitative model-based reasoning
ACM Transactions on Modeling and Computer Simulation (TOMACS)
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Discrete-event systems are used to model a number of engineering applications ranging from performance analysis of large scale communication networks, computer-aided-design (CAD) of circuits to simulation of manufacturing systems. Except for a small set, these systems are analytically intractable and in addition prohibitive to evaluate numerically. Simulation of such complex systems is exceedingly slow to run (and also to develop). Therefore, the development of simulation speedup methods is of crucial importance in its potential of making feasible the evaluation of a vastly larger set of engineering systems.New analytical models are proposed for the analysis of asynchronous, distributed simulation of discrete-event systems. Vectored distributed simulation and a new rollback algorithm, Wolf, are examined in this framework and comparison with existing systems is attempted. A number of examples illustrate the advantages to such a realization of distributed simulation. Implementation of our algorithms on a distributed computing system confirm analytical results predicting a considerable reduction in error propagation, and an enhancement in forward computation.